[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

studio/backend/models/inference.py

@@ -1491,8 +1491,8 @@ class DiffusionLoadRequest(BaseModel):
 # in the C++ layer. uint64 is also routinely cited online so accept
 # any value the underlying RNG could store and bounce the rest at the
 # Pydantic layer with a clean error.
-_SEED_MIN = -(2 ** 63)
-_SEED_MAX = (2 ** 64) - 1
+_SEED_MIN = -(2**63)
+_SEED_MAX = (2**64) - 1
 
 
 class DiffusionGenerateRequest(BaseModel):

studio/backend/routes/training.py

@@ -292,9 +292,7 @@ async def start_training(
 
             llama_backend = get_llama_cpp_backend()
             if getattr(llama_backend, "is_loaded", False):
-                logger.info(
-                    "Unloading GGUF chat model to free GPU memory for training"
-                )
+                logger.info("Unloading GGUF chat model to free GPU memory for training")
                 llama_backend.unload_model()
         except Exception as e:
             logger.warning("Could not unload GGUF chat model: %s", e)

studio/backend/tests/test_diffusion_routes.py

@@ -217,7 +217,7 @@ def test_generate_rejects_oversize_seed(app_with_stub):
     )
     r = c.post(
         "/api/inference/images/generate",
-        json = {"prompt": "x", "seed": 2 ** 100},
+        json = {"prompt": "x", "seed": 2**100},
     )
     assert r.status_code == 422, r.text
 
@@ -234,7 +234,7 @@ def test_generate_accepts_uint64_max_seed(app_with_stub):
     )
     r = c.post(
         "/api/inference/images/generate",
-        json = {"prompt": "x", "seed": (2 ** 64) - 1},
+        json = {"prompt": "x", "seed": (2**64) - 1},
     )
     # The fake backend returns 200 on success; we only care that the
     # request did NOT 422 on seed bounds.